Modern R Programming Cookbook Ebook
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Publication Date: October 2017
File Size: 3134 Kbytes
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Recipes for emerging developers in R programming and data scientists to simplify their R programming capabilities About This Book • Develop strategies to speed up your R code • Tackle programming problems and explore both functional and object-oriented programming techniques • Learn how to address the core problems of programming in R with the most popular R packages for common tasks Who This Book Is For This book is for developers who would like to enhance the R programming skills. Basic knowledge of R programming is assumed. What You Will Learn • Install R and its various IDE for a given platform along with installing libraries from different repositories and version control • Learn about basic data structures in R and how to work with them • Write customized R functions and handle recursions, exceptions in R environments • Create the data processing task as a step by step computer program and execute using dplyr • Extract and process unstructured text data • Interact with database management system to develop statistical applications • Formulate and implement parallel processing in R In Detail R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications. Style and approach This book will be a companion for R programmer and emerging developers in R programming areas. This book will contain recipes related to advanced R programming which will enable users to solve complex problems efficiently.
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